Inverse Problems' 25th year of publication
Bibliographic record
Abstract
2009 is Inverse Problems ' 25th year of publication. In this quarter-century, the journal has established itself as the premier publication venue for inverse problems research. It has matured from its beginnings as a niche journal serving the emerging field of inverse and ill-posed problems to a monthly publication in 2009 covering all aspects of a well-established, vibrant and still-expanding subject. Along with its core readership of pure and applied mathematicians and physicists, Inverse Problems has become widely known across a broad range of researchers in areas such as geophysics, optics, radar, acoustics, communication theory, signal processing and medical imaging, amongst others. The journal's appeal to the inverse problems community and those researchers from the varied fields that encounter such problems can be attributed to our commitment to publishing only the very best papers, and to offering unique services to the community. Besides our regular research papers, which average a remarkably short five months from submission to electronic publication, we regularly publish heavily cited topical review papers and topic-specific special sections, which first appeared in 2004. These highly-downloaded invited articles focus on the latest developments and hot topics in all areas of inverse problems. No other journal in the field offers these features. I am very pleased to take Inverse Problems into its 25th year as Editor-in-Chief. The journal has an impressive tradition of scholarship, established at its inception by the founder and first Editor-in-Chief, Professor Pierre Sabatier. Professor Sabatier envisioned the journal in 1985 as providing a medium for publication of exemplary research in our intrinsically interdisciplinary field. I am glad to say that the support of our authors, readers, referees, Editors-in-Chief, Editorial Boards and Advisory Panels over the years, has resulted in Inverse Problems becoming the top publication in this field, publishing innovative and authoritative research year after year. I expect this tradition of excellence to continue for the next 25 years and beyond, and I look forward to seeing the journal and the community it serves continue to flourish. William W Symes Editor-in-Chief
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.175 | 0.128 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".